瞿明凯-中国科学院大学-UCAS

瞿明凯，男，博士，副研究员，中国科学院青年创新促进会成员。2012年7月获华中农业大学资源环境信息工程专业博士学位；2012年7月 ~ 2014年6月在中国科学院南京土壤研究所做博士后；2014年7月留所工作；2018年10月 ~ 2019年10月在美国康涅狄格大学地理系做访问学者。主要从事区域土壤环境信息、土壤污染时空预测模拟与来源解析方面的研究。取得主要成果如下：[1]提出了一套基于多源信息融合的环境属性快速获取与高精度空间预测方法体系，以及一套土壤环境承载力高精度核算框架，服务于土壤环境的精准管理；[2]针对土壤污染物来源复杂且空间变异性强的特点，将传统源解析受体模型从变量空间拓展到地理空间，并提出了融合多源辅助信息的稳健空间受体模型，服务于土壤环境的精准监测。在J. Hazard. Mater.、Environ. Pollut.、Sci. Total Environ.、Geoderma、Catena、SSSAJ、Ecol. Indic.、GISci. Remote Sens.、土壤学报、生态学报、中国环境科学等主流刊物，以(唯一)第一/通讯作者发表文章46篇(其中SCI文章37篇)。获得软件著作权7项，申请发明专利2项。近年来，主持国家自然科学基金、国家重大研发专项子课题、国家重点研发子课题、江苏省自然科学基金等13项。电子邮件：qumingkai@issas.ac.cn

研究领域

区域土壤环境信息

土壤污染时空预测模拟与来源解析

代表论著

[1] Qu M.K., Song X.D.*, Diao, J.P., Guang X., Huang B., Zhao Y.C., Wang Y.J., 2026. A three-stage framework for spatial prediction of soil heavy metal(loid)s: Integrating in-situ FPXRF calibration, source apportionment, and refined land-use effects. Geoderma. 471. https://doi.org/10.1016/j.geoderma.2026.117868.

[2] Qu M.K.*, Diao, J.P., Guang X., Huang B., Zhao Y.C., Wang Y.J., 2025. Source apportionment of soil heavy metal(loid)s: A robust spatial receptor model integrating AERMOD-simulated atmospheric deposition contributions and land-use effects. Journal of Hazardous Materials. 503. https://doi.org/10.1016/j.jhazmat.2026.141185.

[3] Qu M.K.*, Wu S.J., Guang X., Huang B., Zhao Y.C., 2025. High-accuracy spatial prediction of soil pollutants and their speciation in strong human-affected areas. Journal of Hazardous Materials. 483. https://doi.org/10.1016/j.jhazmat.2024.136684.

[4] Qu M.K.*, Guang X., Wu S.J., Zhao Y.C., Huang B., Wang Y.J., 2024. Determining the net input fluxes of pollutants based on the spatial source apportionment receptor model for early warning of regional soil pollution. Journal of Hazardous Materials. 471. 134409. https://doi.org/10.1016/j.jhazmat.2024.134409.

[5] Qu M.K.*, Guang X., Jian C., Zhao Y.C., Huang B., Wang M.E., Wang H.M., Wang Y.J., 2024. Soil environmental carrying capacity and its spatial high-precision accounting framework. Science of The Total Environment. 938. https://doi.org/10.1016/j.scitotenv.2024.173620.

[6] Guang X., Qu M.K.*, Liu M.S., Chen J., Zhao Y.C., Huang B., 2023. Improving assessment quality of soil natural attenuation capacity at the point and regional scales. Environmental Monitoring and Assessment. 195. https://doi.org/10.1007/s10661-023-11904-4.

[7] Kang J.F., Liu M.S., Qu M.K.*, Guang X., Chen J., Zhao Y.C., Huang B., 2023. Identifying the potential soil pollution areas derived from the metal mining industry in China using MaxEnt with mine reserve scales (MaxEnt_MRS). Environmental Pollution. 329. https://doi.org/10.1016/j.envpol.2023.121687.

[8] Guang X., Chen J., Qu M.K.*, Liu H.B., Zhao Y.C., Huang B., 2022. Effects of mining on the potentially toxic elements in the surrounding soils in China: A meta-analysis. Science of the Total Environment. 153562. https://doi.org/10.1016/j.scitotenv.2022.153562.

[9] Chen J., Qu M.K.*, Wang Y., Huang B., Zhao Y.C., 2022. A joint standard-exceeding risk assessment of multiple pollutants based on robust geostatistics with categorical land-use type data: A case study of soil nitrogen and phosphorus. Environmental Pollution. 118901. https://doi.org/10.1016/j.envpol.2022.118901.

[10] Qu M.K., Liu H.B., Guang X., Chen J., Zhao Y.C., Huang B.*, 2022. Improving correction quality for in-situ portable X-ray fluorescence (PXRF) using robust geographically weighted regression with categorical land-use types at a regional scale. Geoderma. 409. https://doi.org/10.1016/j.geoderma.2021.115615.

[11] Qu M.K., Guang X., Li J.F., Liu H.B., Zhao Y.C., Huang B.*, 2022. An integrated yield-based methodology for improving soil nutrient management at a regional scale. Agronomy. https://doi.org/10.3390/agronomy12020298.

[12] Qu M.K.*, Guang X., Liu H., Zhao Y.C., Huang B., 2021. Incorporating auxiliary data of different spatial scales for spatial prediction of soil nitrogen using robust residual cokriging (RRCoK). Agronomy 11. https://doi.org/10.3390/agronomy11122516.

[13] Qu M.K.*, Guang X., Liu H., Zhao Y.C., Huang B., 2022. Additional sampling using in-situ portable X-ray fluorescence (PXRF) for rapid and high-precision investigation of soil heavy metals at a regional scale. Environmental Pollution. 118324. https://doi.org/10.1016/j.envpol.2021.118324.

[14] Chen J., Zhang J.L., Qu M.K.*, Yang, N., Zhao Y.C., Huang B., 2021. Pollution characteristics and risk assessment of soil heavy metals in the areas affected by the mining of metal-bearing minerals in southwest China. Bulletin of Environmental Contamination and Toxicology. 107, 1070–1079. https://doi.org/10.1007/s00128-021-03378-2.

[15] Qu M.K.*, Guang X., Zhao Y.C., Huang B., 2021. Spatially apportioning the source-oriented ecological risks of soil heavy metals using robust spatial receptor model with land-use data and robust residual kriging. Environmental Pollution. 117261. https://doi.org/10.1016/j.envpol.2021.117261.

[16] Chen J., Qu M.K.*, Zhang J.L., Xie E.Z., Zhao Y.C., Huang B., 2021. Soil fertility quality assessment based on geographically weighted principal component analysis (GWPCA) in large-scale areas. Catena. 105197. https://doi.org/10.1016/j.catena.2021.105197.

[17] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2021. Resampling with in situ ﬁeld portable X-ray ﬂuorescence spectrometry (FPXRF) to reduce the uncertainty in delineating the remediation area of soil heavy metals. Environmental Pollution. 116310. https://doi.org/10.1016/j.envpol.2020.116310.

[18] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2021. Source apportionment of soil heavy metals using robust spatial receptor model with categorical land-use types and RGWR-corrected in-situ FPXRF data. Environmental Pollution. 116220. https://doi.org/10.1016/j.envpol.2020.116220.

[19] Chen J., Qu M.K.*, Zhang J.L., Xie E.Z., Zhao Y.C., Huang B., 2021. Improving the spatial prediction accuracy of soil available nitrogen using geographically weighted principal component analysis-geographically weighted regression kriging (GWPCA-GWRK). Soil Science Society of America Journal. https://doi.org/10.1002/saj2.20189.

[20] Zhang J.L., Wang Y., Qu M.K.*, Chen J., Yang L.F., Huang B., Zhao Y.C., 2020. Source apportionment of soil nitrogen and phosphorus based on robust residual kriging and auxiliary soil-type map in Jintan County, China. Ecological Indicators. 106820. https://doi.org/10.1016/j.ecolind.2020.106820.

[21] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Enhancing apportionment of the point and diffuse sources of soil heavy metals using robust geostatistics and robust spatial receptor model with categorical soil-type data. Environmental Pollution. 114964. https://doi.org/10.1016/j.envpol.2020.114964.

[22] Qu M.K.*, Chen J., Huang B., Zhao Y.C., 2020. Exploring the spatially varying relationships between cadmium accumulations and the main influential factors in the rice-wheat rotation system in a large-scale area. Science of the Total Environment. 139565. https://doi.org/10.1016/j.scitotenv.2020.139565.

[23] Liu G., Liu B., Yang L., Hu W., Qu M.K.*, Lu F., Huang B., 2020. Using pXRF to assess the accumulation, sources, and potential ecological risk of potentially toxic elements in soil under two greenhouse vegetable production systems in North China. Environmental Science and Pollution Research. 27, 11105–11115. http://dx.doi.org/10.1007/s11356-020-07674-y.

[24] Qu M.K.*, Chen J., Li W.D., Zhang C.R., Wan M.X., Huang B., Zhao Y.C., 2019. Correction of in-situ portable X-ray fluorescence (PXRF) data of soil heavy metal for enhancing spatial prediction. Environmental Pollution. 112993. https://doi.org/10.1016/j.envpol.2019.112993.

[25] Qu M.K.*, Wang Y., Huang B.*, Zhao Y.C., 2018. Spatial uncertainty assessment of the environmental risk of soil copper using auxiliary portable X-ray ﬂuorescence spectrometry data and soil pH. Environmental Pollution. 240: 184-190. https://doi.org/10.1016/j.envpol.2018.04.118.

[26] Qu M.K.*, Wang Y., Huang B.*, Zhao Y.C., 2018. Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model. Science of the Total Environment. 626: 203-210. https://doi.org/10.1016/j.scitotenv.2018.01.070.

[27] Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2016. Spatial assessment of soil nitrogen availability and varying effects of related main soil factors on soil available nitrogen. Environmental Science: Processes & Impacts. 18(11): 1449-1457. https://doi.org/10.1039/c6em00407e.

[28] Qu M.K.*, Li W.D., Zhang C.R., Huang B., Zhao Y.C., 2015. Assessing the pollution risk of soil Chromium based on loading capacity of paddy soil at a regional scale. Scientific Reports. 5: 18451. https://doi.org/10.1038/srep18451.

[29] Qu M.K., Huang B.*, Li W.D., Zhang C.R., Zhao Y.C., 2015. Spatial uncertainty of joint health risk of multiple trace metals in rice grain in Jiaxing city, China. Environmental Science: Processes & Impacts. 17(1): 120-130. https://doi.org/10.1039/c4em00513a.

[30] Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2014. Spatially nonstationary relationships between copper accumulation in rice grain and some related soil properties in paddy fields at a regional scale. Soil Science Society of America Journal. 78(5): 1765–1774. https://doi.org/10.2136/sssaj2014.02.0067.

[31] Qu M.K., Li W.D., Zhang C.R., Zhao Y.C.*, Huang B., Sun W.X., Hu W.Y., 2013. Comparison of Three Methods for Soil Fertility Quality Spatial Simulation with Uncertainty Assessment. Soil Science Society of America Journal. 77(6): 2182-2191. https://doi.org/10.2136/sssaj2013.05.0177.

[32] Qu M.K., Li W.D.*, Zhang C.R., 2014. Spatial distribution and uncertainty assessment of potential ecological risks of soil heavy metals using sequential Gaussian simulation. Human and Ecological Risk Assessment: An International Journal. 20(3): 764-778. https://doi.org/10.1080/10807039.2013.770352.

[33] Qu M.K., Li W.D., Zhang C.R., Huang B.*, Zhao Y.C., 2014. Estimating the pollution risk of cadmium in soil using a composite soil environmental quality standard. Scientific World Journal. 750879. http://dx.doi.org/10.1155/2014/750879.

[34] Qu M.K.*, Li W.D., Zhang C.R., Wang S.Q., Yang Y., He L.Y., 2013. Source apportionment of heavy metals in soils using multivariate statistics and geostatistics. Pedosphere. 23(4): 437-444. http://dx.doi.org/10.1016/S1002-0160(13)60036-3.

[35] Qu M.K., Li W.D.*, Zhang C.R., 2013. Assessing the spatial uncertainty in soil nitrogen mapping through stochastic simulations with categorical land use information. Ecological Informatics. 16: 1-9. http://dx.doi.org/10.1016/j.ecoinf.2013.04.001.

[36] Qu M.K., Li W.D.*, Zhang C.R., 2013. Assessing the risk costs in delineating soil nickel contamination using sequential Gaussian simulation and transfer functions. Ecological Informatics. 13: 99-105. http://dx.doi.org/10.1016/j.ecoinf.2012.06.005.

[37] Qu M.K., Li W.D.*, Zhang C.R., Wang S.Q.*, 2012. Effect of Land Use Types on the Spatial Prediction of Soil Nitrogen. GIScicence & Remote Sensing. 49(3): 397-411. http://dx.doi.org/10.2747/1548-1603.49.3.397.

[38] Qu M.K., Li W.D.*, Zhang C.R., Zhao Y.C., Huang B., 2014. County-Scale Spatial Variability of Macronutrient Availability Ratios in Paddy Soils. Applied and Environmental Soil Science. 689482. http://dx.doi.org/10.1155/2014/689482.

[39] 瞿明凯*，李卫东，张传荣，黄标，胡文友，2013．基于受体模型和地统计学相结合的土壤镉污染源解析．中国环境科学．33(5): 854-860.

[40] 瞿明凯，李卫东*，张传荣，黄标，2014．地理加权回归及其在土壤和环境科学上的应用前景．土壤．46(1): 15-22.

[41] 李锦芬，瞿明凯*，黄标，刘刚，赵永存，孙维侠，胡文友．2017．区域土壤CEC与相关控制因子的空间非平稳关系评估．土壤学报．54(3): 638-646. http://dx.doi.org/10.11766/trxb201606300245.

[42] 李锦芬，瞿明凯*，刘刚，黄标．2018．县域尺度土壤铜的有效性及相关影响因素评估．环境科学．39(1): 363-370．http://dx.doi.org/10.13227/j.hjkx.201705182.

[43] 王燕，瞿明凯*，陈剑，杨兰芳，黄标，赵永存．2019．基于GWRK的土壤有效磷空间预测及其超标风险评估．中国环境科学．39: 245-256. http://dx.doi.org/10.19674/j.cnki.issn1000-6923.2019.0031.

[44] 陈剑，瞿明凯*，王燕，万梦雪，黄标，赵永存．2019．长三角平原区县域土壤磷素流失风险及其空间不确定性的快速评估．生态学报．39(24): 9131-9142．http://dx.doi.org/10.5846/stxb201810072156.

[45] 刘宏波，瞿明凯*，张健琳，康俊锋，赵永存，黄标．2021．土壤污染物源解析技术研究进展．环境监控与预警．13(1): 1-7. http://dx.doi.org/10.3969/j.issn.1674-6732.2021.01.001.

[46] 张健琳，瞿明凯*，陈剑，杨兰芳，赵永存，黄标．2021．中国西南地区金属矿开采对矿区土壤重金属影响的Meta分析．环境科学．42(6): 345-352．http://dx.doi.org/10.13227/j.hjkx.202012226.